基于KMV的上市公司信用风险度量实证研究

发布时间：2018-03-09 18:05

本文选题：信用风险　切入点：KMV模型　出处：《江西财经大学》2014年硕士论文　论文类型：学位论文

【摘要】：在我国商业银行所面临的风险中,信用风险无疑是其中最为重要的一种,来自外部的竞争和银行自身已有的不良资产的状况,使信用风险管理水平的提高成为我国银行业面临的重要课题。对于我国的商业银行而言,比较薄弱的环节就是在模型的量化管理方面,所以,信用风险的研究,信用风险度量模型的建立,以及准确地定量分析所面临的信用风险,已经是商业银行提高经营管理水平,降低信用风险的最基本、最迫切的要求。本文第一章主要论述了文章的背景及意义、文章的结构、主要的内容和研究方法。第二章则主要通过分析,比较了几种主要的信用风险模型的优缺点,同时结合我国的实际,阐述了各个信用模型对我国商业银行的适用性。第三章介绍了KMV信用风险管理模型的理论原理以及根据我国现有实际情况的做出了修正,在借鉴国内外经验的基础上,同时结合我国的实际情况,构建出了我国的KMV模型,在此基础上我们试图解决如何用KMV模型去有效地度量我国上市公司信用风险的问题。第四章是文章的实证部分,是文章的核心部分,针对中国证券市场股改已基本完成,市场对公司价值发现效率进一步提高,股价反映公司价值信息进一步增强的实际情况,运用KMV模型基于市场价格变动信息评价我国上市公司的信用风险已比较适合,根据中国上市公司的特殊性,运用修正后的KMV模型评价ST公司和非ST公司在三年时间内的信用风险,并检验模型识别风险的能力,结果表明此模型能较好地识别此两类公司的信用风险,KMV模型使用违约距离计量上市公司的信用风险的方法是可行的。通过实证研究发现：可以运用修正后的KMV模型对上市公司信用风险进行度量和管理。具体结论为：1.通过对ST公司和其匹配的非ST公司进行实证分析发现,由于我国数据库的缺失,在现阶段经验的EDF还是没有办法得出,而采用理论违约概率得出的结论与实际上的情况很不一致,所以理论违约概率在识别上市公司的信用风险方面的作用甚微,只能通过违约距离来识别商业银行的信用风险；2.文章通过实证,在第四章对上市公司ST前两年半的数据进行分析,发现用理论违约概率来识别我国上市公司的信用风险是不可行的,但得出了违约距离可以很好识别信用风险的结论,发现在被ST前两年时,ST和非ST在违约距离方面是有显著差异的；3.同时发现在KMV模型中违约距离在前在三年中是不断下降的,得出了KMV模型提前两年就可以预测到信用风险的变化。本文重点说明了KMV模型参数的估值方法以及实际应用。根据我国金融市场的实际情况对KMV模型作出了改进和修正,可能的创新点包括：1.通过我国上市公司的具体数据得出违约点水平。2.利用KMV模型适合度量上市公司信用风险的特点,同时结合我国上市公司的具体数据,用修正后的KMV模型来度量我国上市公司的信用风险。
[Abstract]:Among the risks faced by commercial banks in our country, credit risk is undoubtedly the most important one. The external competition and the non-performing assets of the banks themselves are the most important. To improve the level of credit risk management has become an important issue for our banking industry. For our commercial banks, the relatively weak link is in the quantitative management of the model, so, the study of credit risk, The establishment of the credit risk measurement model and the accurate quantitative analysis of the credit risk are the most basic for the commercial banks to improve the management level and reduce the credit risk. The first chapter mainly discusses the background and significance of the article, the structure of the article, the main content and research methods. The second chapter compares the advantages and disadvantages of several main credit risk models. At the same time, combined with the reality of our country, the applicability of each credit model to our commercial banks is expounded. Chapter three introduces the theory and principle of KMV credit risk management model and makes a revision according to the actual situation of our country. On the basis of drawing lessons from domestic and foreign experience and combining the actual situation of our country, the KMV model of our country is constructed. On this basis, we try to solve the problem of how to use KMV model to effectively measure the credit risk of listed companies in China. Chapter 4th is the empirical part and the core part of the article. The efficiency of market value discovery is further improved, and the stock price reflects the actual situation of further enhancement of company value information. It is more appropriate to use KMV model to evaluate the credit risk of listed companies in China based on market price change information. According to the particularity of listed companies in China, the modified KMV model is used to evaluate the credit risk of St company and non-St company in three years, and to test the ability of the model to identify the risk. The results show that it is feasible to use this model to measure the credit risk of listed companies by using the default distance. It is found that the modified KMV model can be used to measure the credit risk of listed companies. The concrete conclusion is: 1.The empirical analysis of St company and its matched non-St company shows that, Because of the lack of database in our country, there is still no way to get the EDF experience at the present stage, but the conclusion obtained by using the theory default probability is very inconsistent with the actual situation. Therefore, the probability of theoretical default has little effect on identifying the credit risk of listed companies, so it can only identify the credit risk of commercial banks by default distance. In Chapter 4th, the author analyzes the data of the first two and a half years of St of listed companies, and finds that it is not feasible to identify the credit risk of listed companies by using the probability of theoretical default, but the conclusion is drawn that the distance of breach of contract can identify the credit risk of listed companies very well. It was found that there was significant difference between St and non-ST in the distance of default in the first two years of St. It was also found that in the KMV model, the distance of default decreased continuously in the previous three years. It is concluded that the KMV model can predict the change of credit risk two years in advance. This paper mainly explains the estimation method of the parameters of KMV model and its practical application. According to the actual situation of our country's financial market, the KMV model is improved and modified. The possible innovations include: 1. Through the specific data of listed companies in China, the level of default point is obtained. 2.Using KMV model to measure the characteristics of credit risk of listed companies, and combining with the specific data of listed companies in China, The modified KMV model is used to measure the credit risk of listed companies in China.
【学位授予单位】：江西财经大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F224;F832.4

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